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Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization

The selection criteria play an important role in the portfolio optimization using any ratio model. In this paper, the authors have considered the mean return as profit and variance of return as risk on the asset return as selection criteria, as the first stage to optimize the selected portfolio. Fur...

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Main Authors: Zaheer, Kashif, Abd. Aziz, Mohd. Ismail, Kashif, Amber Nehan, Raza, Syed Muhammad Murshid
Format: Article
Language:English
Published: Penerbit UTM Press 2018
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/85077/1/MohdIsmailAbdAziz2018_TwoStagePortfolioSelectionandOptimizationModel.pdf
http://eprints.utm.my/id/eprint/85077/
http://dx.doi.org/10.11113/matematika.v34.n1.1001
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spelling my.utm.850772020-02-29T13:43:16Z http://eprints.utm.my/id/eprint/85077/ Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization Zaheer, Kashif Abd. Aziz, Mohd. Ismail Kashif, Amber Nehan Raza, Syed Muhammad Murshid QA Mathematics The selection criteria play an important role in the portfolio optimization using any ratio model. In this paper, the authors have considered the mean return as profit and variance of return as risk on the asset return as selection criteria, as the first stage to optimize the selected portfolio. Furthermore, the sharp ratio (SR) has been considered to be the optimization ratio model. In this regard, the historical data taken from Shanghai Stock Exchange (SSE) has been considered. A metaheuristic technique has been developed, with financial tool box available in MATLAB and the particle swarm optimization (PSO) algorithm. Hence, called as the hybrid particle swarm optimization (HPSO) or can also be called as financial tool box particle swarm optimization (FTB-PSO). In this model, the budgets as constraint, where as two different models i.e. with and without short sale, have been considered. The obtained results have been compared with the existing literature and the proposed technique is found to be optimum and better in terms of profit. Penerbit UTM Press 2018 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/85077/1/MohdIsmailAbdAziz2018_TwoStagePortfolioSelectionandOptimizationModel.pdf Zaheer, Kashif and Abd. Aziz, Mohd. Ismail and Kashif, Amber Nehan and Raza, Syed Muhammad Murshid (2018) Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization. Matematika, 34 (1). pp. 125-141. ISSN 0127-8274 http://dx.doi.org/10.11113/matematika.v34.n1.1001
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Zaheer, Kashif
Abd. Aziz, Mohd. Ismail
Kashif, Amber Nehan
Raza, Syed Muhammad Murshid
Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization
description The selection criteria play an important role in the portfolio optimization using any ratio model. In this paper, the authors have considered the mean return as profit and variance of return as risk on the asset return as selection criteria, as the first stage to optimize the selected portfolio. Furthermore, the sharp ratio (SR) has been considered to be the optimization ratio model. In this regard, the historical data taken from Shanghai Stock Exchange (SSE) has been considered. A metaheuristic technique has been developed, with financial tool box available in MATLAB and the particle swarm optimization (PSO) algorithm. Hence, called as the hybrid particle swarm optimization (HPSO) or can also be called as financial tool box particle swarm optimization (FTB-PSO). In this model, the budgets as constraint, where as two different models i.e. with and without short sale, have been considered. The obtained results have been compared with the existing literature and the proposed technique is found to be optimum and better in terms of profit.
format Article
author Zaheer, Kashif
Abd. Aziz, Mohd. Ismail
Kashif, Amber Nehan
Raza, Syed Muhammad Murshid
author_facet Zaheer, Kashif
Abd. Aziz, Mohd. Ismail
Kashif, Amber Nehan
Raza, Syed Muhammad Murshid
author_sort Zaheer, Kashif
title Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization
title_short Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization
title_full Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization
title_fullStr Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization
title_full_unstemmed Two Stage Portfolio Selection and Optimization Model with the Hybrid Particle Swarm Optimization
title_sort two stage portfolio selection and optimization model with the hybrid particle swarm optimization
publisher Penerbit UTM Press
publishDate 2018
url http://eprints.utm.my/id/eprint/85077/1/MohdIsmailAbdAziz2018_TwoStagePortfolioSelectionandOptimizationModel.pdf
http://eprints.utm.my/id/eprint/85077/
http://dx.doi.org/10.11113/matematika.v34.n1.1001
_version_ 1662754347990122496
score 13.211869

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